I started with a simple idea: give AI fake money, let it study crypto, and see whether it could find trades worth making. I called the target Grok Bot because that was the closest picture I had in my head.
The more we built, the less it looked like one bot. It started looking like a tiny trading company. A Librarian finds claims. A researcher turns claims into exact rules. A tester tries to break those rules against old data. A skeptic looks for cheating and bad assumptions. A paper desk handles fake orders. Ordinary software—not an AI opinion—owns risk and the ledger.
I am still the boss
I sit at the top as the Principal. Codex helps me build and commission the place. A Chief of Staff keeps work moving between the agents. That chain matters because an agent should not be able to promote its own idea, change the risk rules, and then grade itself.
The machine runs on three separate virtual computers. Research gets room to make a mess. Control assigns work. The core keeps records and paper money. The workers talk through narrow doors instead of sharing every password and folder.
The boring parts are the useful parts
Every handoff has an owner, evidence, a due date, and an acceptance test. Every paid model call gets counted. Every accepted, rejected, skipped, and closed signal becomes a record. If the market data is stale or two systems disagree, the correct answer is to do nothing.
I want AI to come up with ideas. I do not want it making up reality.
There are no real orders in this system. If it ever earns that right, the first real-money version will recommend a trade and wait for me to make it myself.